Instructions to use gavrilstep/85aa9e5d-cbb6-4fe6-9e71-d69f333295b0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gavrilstep/85aa9e5d-cbb6-4fe6-9e71-d69f333295b0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Theta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "gavrilstep/85aa9e5d-cbb6-4fe6-9e71-d69f333295b0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e90fc861eca708a5a7c3de1c18d096e325bae6c1d5abec6c6b1d367d112ac022
- Size of remote file:
- 1.06 kB
- SHA256:
- 017f7d123df6134e490bc0a4b797f60b72418d2b0df64facc9dfb4c2e38ddeb5
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